How can Indian MSMEs automate their finance functions?

MSMEs (Micro, Small and Medium Enterprises) contribute close to 30% of the country’s GDP, according to a report by the World Economic Forum report Transforming Small Businesses: An AI Playbook for India’s SMEs.

The sector employs over 230 million people, and drives almost half of India’s exports. Its health and growth are therefore central to India’s ambition of becoming a $7 trillion economy by 2030.

The report also indicates that AI-led transformation across the MSME ecosystem could unlock more than $490 billion in economic value. But despite its potential, adoption remains low. 

While MSMEs understand that AI can bring efficiencies, many remain unsure how to implement it, or even where to begin. 

“MSMEs are impacted by fundamental structural issues which become impediments for AI adoption,” Cheruku Srikanth, Founder and CEO at Digital CFO, tells SMBStory.

Challenges 

Srikanth points out that MSMEs face basic structural challenges that prevent effective AI adoption. 

First, the processes are manual and error-prone, making real-time data use difficult. Most lack proper financial controls and maker–checker systems, leading to missed errors and compliance issues. 

“Without structured bookkeeping, accounting and financial management processes which are implemented on a consistent basis, MSMEs cannot attain uniformity in transaction output, and the corresponding data is not viable for AI automation,” he adds. 

Bookkeeping forms the base for accurate accounting and financial reporting. Errors at this stage ripple upstream, distorting ledgers, compliance filings, cash-flow statements, and management insights. 

Secondly, MSMEs struggle with talent. “Good talent typically gravitates to larger organisations, hence, MSMEs struggle to manage…Many MSMEs still struggle with foundational digitisation.”

In other words, a significant portion of MSMEs are still trying to set up the basics before they can even think about automation, let alone AI.

Start with the basics

Automation and AI are only as good as the data fed into them. 

For many MSMEs, the biggest leakage point is bookkeeping itself. This includes disorganised ledgers, missing receipts, ad-hoc journal entries, and a lack of controls.

According to a 2024 report by the Ministry of MSME, nearly 65% of MSMEs still use traditional bookkeeping, but digital adopters report 40% better cash flow management and 30% fewer compliance errors.

When MSMEs start exploring automation, they often encounter advanced fintech tools built by engineers with limited knowledge or understanding of the on-ground bookkeeping realities. 

“They expect MSMEs to implement these AI tools on data which is filled with errors and reconciliation issues,” Srikanth says.

Digitisation must therefore begin at the core, that is, at bookkeeping. “It will then help generate real-time, accurate, compliant, and reliable data for upstream value addition using AI,” he adds.

Zoho, Xero, NetSuite, oodo, and QuickBooks are some of the new-age tools for accounting. 

Srikanth also notes that legacy systems like Tally require prior accounting knowledge and regular human intervention. In many cases, MSMEs’ accounts are handled by cross-functional staff who lack formal training or education. 

“For them, it is important to ensure that there is ease of use in the bookkeeping application and not something which requires them to complete another course before they use the software…Further, if the software version is updated or if there is migration to a new software, these challenges increase.”

The first step, therefore, is choosing digital tools that are simple, integrated, and require minimal manual input, thus, reducing the possibility of human error.

Refining the data

Since accuracy and compliance are the biggest bottlenecks, Srikanth outlines a few steps to building a unified and structured financial data layer:

• Digitise receipts and invoices so transactions are auto-logged, supported by clean vendor, supplier and customer master data.
• Minimise manual intervention and use frictionless tools that maintain data sanctity.
• Ensure structured linkages with government systems for accounting and reporting.
• Use tools capable of reliably auditing bookkeeping output.

The roadmap

He also shares what a realistic, staged roadmap for MSMEs aiming to automate accounting, procurement, cash flow or reconciliations should look like:

• A single integrated platform for bookkeeping, accounting, and financial management, instead of siloed tools.
• Event-based data capture with in-built intelligence that automatically accounts for context such as customer, location, tax logic or inventory.
• Automated internal controls that prevent errors at the point of entry.
• Document and audit trails baked into every transaction.
• Real-time AP (accounts payable)/AR (accounts receivable) automation with continuous reconciliations.

“This creates a clean, accurate, compliant and reliable machine-readable data layer: the foundation of AI,” Srikanth adds.

He further outlines four stages of adoption:

Stage 1: Digital foundation, which includes cloud bookkeeping, automated GST/TDS logic, real-time AR/AP, and built-in controls.

Stage 2: Process automation, which includes reconciliations, invoice processing, workflows, and inventory sync.

Stage 3: Predictive insights comprising cash-flow forecasting, collection prioritisation, procurement and margin analytics

Stage 4: Autonomous finance like AI-assisted transaction processing, anomaly detection, auto-matching and real-time scenario modelling.

Measuring the outcomes

Many MSMEs struggle to define measurable financial goals. Srikanth shares that digitisation can directly improve operational efficiency and even top-line performance. Key metrics to track this include:

• Reduction in turnaround time across bookkeeping and accounting.
• Faster access to insights and decision-making reports.
• Higher accuracy in TDS/GST compliance.
• Timely periodic account closures.
• Better working capital efficiency.
• Shorter reconciliation cycles.

Selecting the right tools

Finally, while global SaaS tools exist, Srikanth notes a gap in the market. “Global tools miss India’s compliance complexity and process fragmentation,” he says. 

An effective India-specific AI finance tool would require:

• Conversational interfaces for non-experts.
• Compliance intelligence for GST, TDS, e-invoicing and audit trails.
• Offline-to-online continuity for low-connectivity regions.
• Multi-stakeholder portals.
• MSME-friendly pricing (under Rs 20,000 annually).

A responsible approach, he adds, must include foundational bookkeeping automation, rule-based AI, not black-box models, human-in-loop approvals, auditability through trace logs, and gradual automation starting with low-risk tasks.

Among the workflows most ready for AI-led automation are ledger posting, GST determination and compliance filing, AR follow-ups, invoice processing, three-way matching, cash-flow prediction, expense claims, inventory valuation, and internal financial controls.

Final word

Srikanth believes India needs an integrated financial data stack for MSMEs, “similar to UPI”. 

He recommends open government standards for compliance systems, real-time data pipes from banks, interoperable APIs from tech providers and capability-building by industry bodies. 

“When all four collaborate, MSME AI adoption can accelerate exponentially,” he says.

He points to AI-led capabilities that will shape MSMEs’ financial future: zero-touch accounting, predictive cash-flow engines, automated internal audit, real-time lending eligibility and AI-driven procurement and pricing analytics.